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Conditional sampling for barrier option pricing under the Heston model

Listed author(s):
  • Nico Achtsis
  • Ronald Cools
  • Dirk Nuyens
Registered author(s):

    We propose a quasi-Monte Carlo algorithm for pricing knock-out and knock-in barrier options under the Heston (1993) stochastic volatility model. This is done by modifying the LT method from Imai and Tan (2006) for the Heston model such that the first uniform variable does not influence the stochastic volatility path and then conditionally modifying its marginals to fulfill the barrier condition(s). We show this method is unbiased and never does worse than the unconditional algorithm. Additionally the conditioning is combined with a root finding method to also force positive payouts. The effectiveness of this method is shown by extensive numerical results.

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    Paper provided by in its series Papers with number 1207.6566.

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    Date of creation: Jul 2012
    Date of revision: Dec 2012
    Handle: RePEc:arx:papers:1207.6566
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